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Data Masking Components: Credit Card Dynamic

Credit Card Dynamic

API Reference CLR Reference

Usage Instructions:


The purpose of the component is to mask credit cards dynamically maintaining consistency across data sets. The algorithm retains the first characters as per issuer and also calculates checksum with the Luhn algorithms.


Referential Integrity Preserving Substitution


The Masking Credit Card component expects a credit card number in a string that consists of integers, e.g.: XXXXXXXXXXXXXXX. There might be separators in between the digits, such as “-“or “/”. It produces a card of the same issuer with the parity digit consistent with Luhn calculation.

API Reference, CLR Reference

Usage Instructions:

1. Configure a source that contains the column with Credit Card value (we assume character data type). The data in the column may also include any characters that will be treated as a separator, such as spaces, dashes and slashes.
2. Drag and Drop Credit Card RandomDynamic masking component, connect the source and the Credit Card Random Dynamic data masking component with the source's precedence constraint:
3. Now, the precedence constraint (the blue arrow) passes proper meta-data to the CC RandomDynamic component. If you click on constraint, you will see:
4. Now that the metadata for the Credit Card exists, and values are passed into the data masking component, please open the component editor:
5. In the second tab, there are input columns. Please check-mark only one column, the one that you will be masking with Credit Card algorithm:
6. This will create an extra column with the prefix “Masked_”.
7. Create a connection manager for the destination and configure source component for the destination. In the connection manager, in the tab “Mappings”, specify that you want newly created Field_Masked to be a field replacing the original value. For that, just click on the available input columns, choose the masked value, and map to the “Available Destination Columns”
8. Now, all the configurations are complete for the valid values. You can run the package with the Credit Card RandomDynamic Data Masking component, and see the results of data masking:

Error Handling

9. If, however, there are invalid values in the package's source, one would need to configure error handling. Invalid values are those that are not conforming to the rules of the entity. To handle invalid values, each data masking component has error handling precedence constraint. One needs to create error destination connection and connect red arrow (error handling constraint) with this destination. As the connection is made, one needs to configure the state of failure: “Fail”,”Ignore” or “Redirect”.
10. It is recommended that one re-directs the output into the error destination, so that later one be able to analyze and process data for quality purposes. The CC RandomDynamic data masking components errors are the only ones not recommended for further processing as it is truly hard to break their format.
11. It is our suggestion that with Credit Card RandomDynamic data masking component one should not process erroneous data without further analysis at all.

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